A mathematical programming model for AGVS planning and control in manufacturing systems
Computers and Industrial Engineering
A simulation study on the performance of pickup-dispatching rules for multiple-load AGVs
Computers and Industrial Engineering
A simulation study of a bi-directional load-exchangeable automated guided vehicle system
Computers and Industrial Engineering
Modelling and Simulation in Engineering
An embedded control system for automatic guided vehicle
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part III
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Pick up-dispatching problem together with delivery-dispatching problem of a multiple-load automated guided vehicle (AGV) system have been studied. By mixing different pick up-dispatching rules, several control strategies (alternatives) have been generated and the best control strategy has been determined considering some important criteria such as System Throughput (ST), Mean Flow Time of Parts (MFTP), Mean Tardiness of Parts (MFTP), AGV Idle Time (AGVIT), AGV Travel Full (AGVTF), AGV Travel Empty (AGVTE), AGV Load Time (AGVLT), AGV Unload Time (AGVUT), Mean Queue Length (MQL) and Mean Queue Waiting (MQW). For ranking the control strategies, a new framework based on MADM methods including fuzzy MADM and TOPSIS method were developed. Then several simulation experiments which had been based on a flow path layout to find the results were conducted. Finally, by using TOPSIS method, the control strategies were ranked. Furthermore, a similar approach was used for determining the optimal fleet size. The main contribution of this paper is developing a new approach combining the top managers' views in selecting the best control strategy for AGV systems while trying to optimize the fleet size at the mean time by combining MADM, MCDM and simulation methods.